no code implementations • 13 Feb 2024 • Aditya Challa, Sravan Danda, Laurent Najman
In this paper, we propose a class of non-parametric classifiers, that learn arbitrary boundaries and generalize well.
no code implementations • 25 Apr 2023 • Aditya Challa, Snehanshu Saha, Soma Dhavala
We argue that between the choice of having a minimum calibration error on original distribution which increases across distortions or having a (possibly slightly higher) calibration error which is constant across distortions, we prefer the latter We hypothesize that the reason for unreliability of deep networks is - The way neural networks are currently trained, the probabilities do not generalize across small distortions.
no code implementations • 2 Aug 2022 • Siddharth Saravanan, Aditya Challa, Sravan Danda
In this article, we develop a robust pipeline based on mathematical morphological (MM) operators that can seamlessly extend any existing semantic segmentation algorithm to high resolution images.
no code implementations • 28 Feb 2022 • Rohan Agarwal, Aman Aziz, Aditya Suraj Krishnan, Aditya Challa, Sravan Danda
In this article, we estimate the edge-weights explicitly and use them for the downstream classification tasks - both semi-supervised and unsupervised.
no code implementations • 30 Oct 2021 • Govind Sharma, Aditya Challa, Paarth Gupta, M. Narasimha Murty
In this article, we investigate this problem in the presence of higher-order relations.
no code implementations • 16 Jul 2021 • Nagajothi Kannan, Sravan Danda, Aditya Challa, Daya Sagar B S
One of the useful geophysical features of a river sub-basin is that of a roughness measure on DEMs.
1 code implementation • 17 Mar 2021 • Aditya Challa, Sravan Danda, B. S. Daya Sagar, Laurent Najman
In this article, we propose to use a watershed classifier.